Somatosensory Feedback for Neuroprosthetics

✍ Scribed by Burak Guclu

• Publisher: Academic Press
• Year: 2021
• Tongue: English
• Leaves: 718
• Edition: 1
• Category: Library

✦ Synopsis

Although somatosensory system works in tandem with the motor system in biology, the majority of the prosthetics research and commercial efforts had focused on accommodating movement deficits. With the development of neuroprostheses in the last 15 years, it has become evident that somatosensory input (mainly as touch and proprioception) is essential for motor control, manipulating objects, and embodiment, in addition to its primary role for sensory perception.

Somatosensory Feedback for Neuroprosthetics covers all relevant aspects to facilitate learning and doing research and development in the field.

To understand the properties of the body to create viable solutions, this book starts with chapters reviewing the basic anatomy, physiology, and psychophysics of the somatosensory system, sensorimotor control, and instrumentation. Some sections are dedicated to invasive (peripheral and central, mainly cortical) and noninvasive (vibrotactile, electrotactile, etc.) approaches. Final chapters cover future technologies such as novel sensors and electrodes, safety, and clinical testing, and help to make up future prospects for this field with an emphasis on development and end use.

With contributions from renowned experts, the contents include their recent findings and technical details necessary to understand those findings.

✦ Table of Contents

Front Cover
Somatosensory Feedback for Neuroprosthetics
Copyright Page
Dedication
Contents
List of contributors
Preface
I. Background and fundamentals
1 Introduction to somatosensory neuroprostheses
1.1 Scope and history of neuroprostheses
1.2 Classification of neuroprostheses
1.3 Basic components of the somatosensory system
1.3.1 Somatosensory receptors and afferent nerves
1.3.2 Central pathways and cortical areas
1.3.3 Psychophysical processing and perception
1.4 Overview of somatosensory neuroprostheses
1.4.1 Noninvasive methods for feedback
1.4.1.1 Vibrotactile stimulation
1.4.1.2 Electrotactile stimulation
1.4.2 Invasive methods for feedback
1.4.2.1 Peripheral nerve stimulation
1.4.2.2 Brain cortex stimulation
1.5 Multidisciplinary approach and future directions
Acknowledgments
References
2 Proprioception: a sense to facilitate action
2.1 Introduction
2.2 Sensors contributing to proprioception
2.2.1 Muscle spindles
2.2.2 Golgi tendon organs
2.3 Proprioceptive coding along the cerebral cortical pathway
2.3.1 Dorsal column pathway
2.3.2 Thalamic proprioceptive encoding
2.3.3 Somatosensory cortex
2.4 Somato-motor connections and control of proprioceptive feedback
2.4.1 Spinal reflexes
2.4.2 Longer latency reflexes and sensorimotor connections
2.4.3 Top-down modulation of proprioceptive signals
2.4.3.1 Control of the fusimotor system
2.4.3.2 Neural sensory gain modulation
2.5 Cerebellar involvement in proprioception
2.5.1 Cerebellar afferent pathway
2.5.2 Sensorimotor adaptation
2.6 Summary
References
3 Electrodes and instrumentation for neurostimulation
3.1 Two fundamental requirements
3.2 Recording and stimulating
3.3 Requirements for efficacy and safety of a stimulating device
3.4 Electrical model of stimulation: the electrode–tissue interface
3.4.1 Physical basis of the electrode–tissue interface
3.4.2 Capacitive/non-Faradaic charge transfer
3.4.3 Faradaic charge transfer and the electrical model of the electrode–electrolyte interface
3.4.4 Reversible and irreversible Faradaic reactions
3.4.5 The origin of electrode potentials and the three-electrode electrical model
3.4.6 Faradaic processes: quantitative description
3.4.7 Charge injection during electrical stimulation: interaction of capacitive and Faradaic mechanisms
3.4.8 Common waveforms used in neural stimulation
3.4.9 Pulse train response and ratcheting
3.4.10 Electrochemical reversal
3.5 Introduction to extracellular stimulation of excitable tissue
3.5.1 Cathodic and anodic stimulation
3.5.2 Exploiting the voltage-gated sodium channel
3.5.3 Quantifying action potential initiation
3.5.4 Bipolar configurations; voltage-controlled stimulation
3.6 Mechanisms of damage
3.6.1 Tissue damage from intrinsic biological processes
3.6.2 Tissue damage from electrochemical reaction products
3.6.3 Multiple contributing factors
3.7 Design compromises for efficacy and safety
3.8 Requirements for efficacy and safety of a recording device
3.9 Electrical model of the recording electrode
3.10 Materials used for stimulating and recording electrodes
3.11 Instrumentation
3.11.1 Stimulation parameters of interest
3.11.2 Recording architecture and parameters of interest
3.11.3 Noise
3.11.4 Common mode rejection
3.11.5 Loading and impedance
References
4 Stimulus interaction in transcutaneous electrical stimulation
4.1 Introduction
4.2 User opinions on sensory feedback
4.3 The role of sensory feedback in motor control
4.3.1 Control policy
4.3.2 Efferent copy
4.3.3 Signal noise
4.3.4 Implications
4.4 Physiology of sensory feedback
4.4.1 Mechanoreceptors
4.4.2 Stimulus interaction
4.5 Event-related feedback in upper-limb prosthetics
4.6 Optimizing event-related feedback strategies
4.6.1 Testing the internal model
4.6.2 Effect of stimulation pattern
4.6.3 Testing stimulus interaction
4.6.3.1 Methods
4.6.3.2 Results
4.6.3.3 Implications for prosthetic control
4.7 Conclusion
References
II. Non-invasive methods for somatosensory feedback and modulation
5 Supplementary feedback for upper-limb prostheses using noninvasive stimulation: methods, encoding, estimation-prediction ...
5.1 Motivation
5.2 Restoration of somatosensory feedback
5.3 Encoding feedback variables using multichannel electrotactile stimulation
5.4 Feeding back the command signal as opposed to its consequences
5.5 Feedback can support predictive and corrective strategies
5.6 Evaluating the role of feedback in the state estimation process
5.7 Concluding remarks
Acknowledgments
References
6 Noninvasive augmented sensory feedback in poststroke hand rehabilitation approaches
6.1 Introduction: sensory information in hand motor performance
6.1.1 Upper limb impairment
6.1.2 Sensorimotor control of the upper limb
6.1.3 Sensory input for optimal movement
6.1.4 Augmented feedback to stimulate neural plasticity
6.2 Current rehabilitation techniques
6.2.1 Approach to rehabilitation
6.2.2 Constraint-induced movement therapy
6.2.3 Mirror therapy
6.2.4 Robot-assisted therapy
6.3 Augmented sensory feedback
6.3.1 Aspects of feedback
6.3.2 Feedback modalities
6.3.3 Strategies for error feedback
6.3.4 Developing a reliance on extrinsic feedback
6.3.5 The sensory side of rehabilitation is an open question
6.3.6 Auditory feedback
6.3.6.1 Relevance of auditory information in motor learning
6.3.6.2 Types of augmented auditory feedback
6.3.6.3 Auditory feedback devices
6.3.6.3.1 Improvements in motor performance
6.3.6.3.2 Improvements in sensory awareness
6.3.6.4 Conclusions on auditory sensory feedback
6.3.7 Visual feedback
6.3.7.1 Relevance of visual information in motor learning
6.3.7.2 Benefits of virtual reality rehabilitation
6.3.7.3 General features of a virtual reality setup
6.3.7.3.1 Movement representation
6.3.7.3.2 Interaction with objects during task performance/training
6.3.7.3.3 Kinematic features recording
6.3.7.4 Studies in virtual reality for rehabilitation purposes
6.3.7.5 Other visual feedback delivery methods
6.3.7.6 Conclusions on visual feedback
6.3.8 Haptic feedback
6.3.8.1 Relevance of haptic information in motor learning
6.3.8.2 Movement-based (implicit) and sensory-based (explicit) haptic feedback
6.3.8.2.1 Implicit haptic feedback
6.3.8.2.2 Explicit haptic feedback: kinesthetic and tactile
6.3.8.2.3 Feedback for kinesthetic illusion
6.3.8.3 Devices for haptics
6.3.8.3.1 Types of augmented haptic stimulation
6.3.8.3.2 Vibrotactile sensory substitution
6.3.8.3.3 Proprioceptive feedback
6.3.8.3.4 Dynamic and performance feedback
6.3.8.4 Conclusions on haptic feedback
6.3.9 Multimodal feedback
6.3.9.1 Multisensory integration in the human brain
6.3.9.2 Studies on multimodal feedback
6.3.9.2.1 Visual and haptic feedback
6.3.9.2.2 Visual and auditory feedback
6.3.9.2.3 Combination of visual, haptic, and auditory feedback
6.3.9.3 Conclusions on multimodal feedback
6.3.10 Sensory information enhancement
6.3.10.1 Vagus nerve stimulation
6.3.10.2 Stochastic resonance
6.3.10.2.1 Optimal noise may benefit rehabilitation
6.3.10.2.2 Studies on stochastic resonance for rehabilitation
6.3.10.2.3 Possible implications in feedback evaluations
6.3.10.3 Conclusion on sensory enhancement
6.4 Future directions for augmented feedback
References
7 Targeted reinnervation for somatosensory feedback
7.1 Introduction
7.2 Targeted reinnervation surgery and mechanisms of somatosensory restoration
7.3 Cutaneous reinnervation: tactile sensation
7.3.1 Neurophysiology of cutaneous targeted sensory reinnervation
7.3.2 Functional use of cutaneous sensory reinnervated sites
7.3.3 The importance of matched feedback: embodiment
7.3.4 Variability in cutaneous reinnervation
7.3.5 State of technology for providing haptic feedback
7.4 Muscle sensory reinnervation: kinesthesia
7.5 Neuropathic pain
7.6 Conclusion
References
8 Transcranial electrical stimulation for neuromodulation of somatosensory processing
8.1 Introduction
8.2 Chapter objectives
8.3 Methods of transcranial electrical stimulation and mechanism of action
8.3.1 Transcranial direct current stimulation
8.3.2 Transcranial alternating current stimulation
8.3.3 Transcranial random noise stimulation
8.3.4 Transcranial pulsed current stimulation
8.4 Experiment results and discussion
8.4.1 Neuromodulation of somatosensory processing by transcranial electrical stimulation
8.4.1.1 Modulation of tactile senses and haptic perception
8.4.1.2 Modulation of proprioception
8.4.1.3 Sensory modulation in stroke patients
8.4.2 Modulating multisensory integration
8.5 Future opportunities
8.6 Conclusions
References
III. Peripheral nerve implants for somatosensory feedback
9 Connecting residual nervous system and prosthetic legs for sensorimotor and cognitive rehabilitation
9.1 Introduction
9.2 Intraneural electrodes
9.2.1 Implantable electrodes
9.2.2 Surgical procedure
9.3 Intraneural electrical stimulation
9.3.1 Characterization of the electrically evoked sensation
9.3.2 Neuroprosthetic leg
9.3.3 Sensory encoding strategy
9.3.4 Sensorimotor integration
9.3.5 Cognitive integration
9.3.6 Health benefits
9.4 Conclusions
References
10 Biomimetic bidirectional hand neuroprostheses for restoring somatosensory and motor functions
10.1 Introduction
10.2 Mechanoreceptors and somatosensory pathways
10.3 Neural interfaces
10.4 Neural stimulation
10.5 Closed-loop system
10.6 Encoding strategies
10.6.1 Linear modulation
10.6.2 Amplitude modulation
10.6.3 Frequency modulation
10.6.4 Biomimetic stimulation
10.7 Neuron models
10.8 Model-based approaches
10.9 Challenges for bidirectional sensory and motor function restoration
10.9.1 Artifact removal for bidirectional neural systems
10.10 Conclusions
References
IV. Cortical implants for somatosensory feedback
11 Restoring the sense of touch with electrical stimulation of the nerve and brain
11.1 Introduction
11.1.1 The importance of touch in manual behavior
11.1.2 Electrical activation of neurons
11.1.3 Neural coding—the language of the nervous system
11.2 Neural basis of touch
11.2.1 Tactile innervation of the skin
11.2.2 Medial lemniscal pathway
11.2.3 Somatosensory cortex
11.3 Electrical interfaces with the nervous system
11.3.1 Targets of neural interfaces
11.3.2 Interface hardware—peripheral
11.3.3 Interface hardware—central
11.4 Shaping artificial touch sensations
11.4.1 Contact location—leveraging somatotopic maps
11.4.2 Contact pressure
11.4.3 Timing of contact events
11.4.4 Sensory quality
11.5 Future horizons
References
12 Intracortical microstimulation for tactile feedback in awake behaving rats
12.1 Introduction
12.2 Behavioral instrumentation and training schedule
12.3 Vibrotactile detection experiments
12.4 Intracortical microstimulation in rats
12.5 Psychophysical correspondence between sensations elicited by vibrotactile and electrical stimulation
12.6 Validation of psychometric equivalence functions
12.7 Behavioral demonstration of a tactile neuroprosthesis in rats
12.8 Conclusions
Acknowledgment
References
13 Cortical stimulation for somatosensory feedback: translation from nonhuman primates to clinical applications
13.1 Introduction
13.2 A brief history of somatosensory neuroprosthetics with nonhuman primates
13.3 Why nonhuman primates are a pertinent model for the development of somatosensory neuroprosthetics
13.4 How nonhuman primate studies can help engineer somatosensory neuroprosthetics
13.4.1 Development of cortical implants
13.4.2 Somatosensory feedback encoding
13.4.3 Validation of computational models
13.5 Experimental setups for somatosensory studies with nonhuman primates
13.5.1 Cortical and intracortical electrical stimulation
13.5.2 Somatosensory inputs
13.5.3 Visual inputs
13.5.4 Behavioral tracking
13.6 Conclusion
References
14 Touch restoration through electrical cortical stimulation in humans
14.1 Introduction
14.1.1 Advantages of cortical stimulation
14.1.2 Current clinical uses of direct cortical stimulation
14.1.3 History of direct cortical stimulation
14.1.4 Direct cortical stimulation and perception in humans
14.2 Stimulation physiology
14.2.1 Sensory processing physiology
14.2.2 Activation of the tactile sensory system via electrical stimulation
14.3 Direct cortical stimulation for sensory feedback and neuroprosthetic control
14.3.1 The perception and psychophysics of direct cortical stimulation
14.3.2 Primary somatosensory cortex direct cortical stimulation parameters and perception
14.3.2.1 Perception
14.3.2.2 Amplitude
14.3.2.3 Pulse width
14.3.2.4 Pulse frequency
14.3.2.5 Charge
14.3.2.6 Train duration
14.3.2.7 Novel stimulation waveforms
14.3.3 Percept localization
14.3.4 Brain state, attention, and perception
14.3.5 Response times
14.3.6 Sensory ownership and the rubber hand illusion
14.3.7 Use of primary somatosensory cortex direct cortical stimulation as task feedback
14.4 Future advances in cortical sensory stimulation
14.4.1 More channels
14.4.2 Concurrent stimulation and recording
14.4.3 Wireless technologies
14.5 Conclusion
References
15 Design of intracortical microstimulation patterns to control the location, intensity, and quality of evoked sensations i...
15.1 Introduction
15.2 Stimulation design
15.2.1 Historical experiments
15.2.2 Electrical effects on neurophysiology
15.3 Parameterization
15.3.1 Sensory brain–machine interfaces
15.3.2 Biomimetic stimulation pattern design
15.3.3 Sensory substitution stimulation
15.3.4 Charge
15.4 Applications in human participants
15.4.1 Cortical surface stimulation
15.4.2 Intracortical microstimulation
15.5 Bidirectional brain–machine interfaces
15.6 Conclusion
References
V. Future technologies
16 Neural electrodes for long-term tissue interfaces
16.1 Introduction
16.2 Peripheral nerve electrodes
16.2.1 Surface electrodes
16.2.2 Extraneural electrodes
16.2.2.1 Cuff electrodes
16.2.2.2 Flat interface nerve electrode
16.2.2.3 Other extraneural electrodes
16.2.3 Intraneural electrodes
16.2.3.1 Longitudinal intrafascicular electrodes
16.2.3.2 Transverse intrafascicular multichannel electrodes
16.2.3.3 Multielectrode arrays
16.2.4 Regenerative electrodes
Acknowledgments
References
17 Challenges in neural interface electronics: miniaturization and wireless operation
17.1 Introduction
17.2 Important aspects of neural interface electronics
17.2.1 Microelectrode array
17.2.2 Data acquisition
17.2.3 Stimulation
17.2.4 Integrated processing on chip
17.2.5 Communication
17.2.6 Power management
17.3 RF solutions for wireless power transfer
17.4 Optical solutions for wireless power transfer
17.4.1 Optical penetration depths for biological tissue for different wavelengths
17.4.2 Laser power limitations for skin
17.5 Ultrasonic solutions for wireless power transfer
17.6 Conclusion
References
18 Somatosensation in soft and anthropomorphic prosthetic hands and legs
18.1 Introduction
18.2 Soft and anthropomorphic prostheses
18.2.1 Upper limb prostheses
18.2.2 Lower limb prostheses
18.3 Sensing techniques in prostheses
18.3.1 Sensing techniques
18.3.1.1 Prosthetic sensors
18.3.1.2 Electronic skins
18.3.2 Applications in upper limb prostheses
18.3.3 Applications in lower limb prostheses
18.4 Outlook and future directions
References
19 Prospect of data science and artificial intelligence for patient-specific neuroprostheses
19.1 Introduction
19.2 Classical machine learning methods for neuroprosthetic applications
19.2.1 Probability theory and evaluation metrics for machine learning models
19.2.1.1 Probability theory
19.2.1.2 Bias and variance
19.2.1.3 The evaluation metrics
19.2.2 Feature selection techniques
19.2.3 Logistic regression
19.2.4 k-Nearest neighbor classifier
19.2.5 Support vector machines
19.2.6 Decision trees
19.2.7 Ensemble methods
19.2.8 Reinforcement learning
19.2.9 Artificial neural networks
19.3 Deep learning methods for neuroprosthetic applications
19.3.1 Convolutional neural networks
19.3.2 Recurrent neural networks
19.4 Conclusion
References
20 Modern approaches of signal processing for bidirectional neural interfaces
20.1 Signal processing in neural signal recording
20.1.1 Generalized signal processing workflow
20.1.2 Preprocessing
20.1.2.1 Denoising of the signal
20.1.2.2 Running observational window analysis
20.1.2.3 Feature extraction and selection
20.1.2.4 Features for classification
20.1.2.5 Feature extraction and selection for clustering
20.1.3 Spike detection
20.1.3.1 Amplitude thresholding
20.1.3.2 Template matching
20.1.3.3 Energy-based spike detection
20.1.3.4 Wavelet-based spike detection
20.1.3.5 Feature selection
20.1.4 Classification and clustering
20.1.4.1 Classification
20.1.4.2 Clustering
20.1.4.3 Combining classification and clustering
20.2 Signal processing in neural stimulation
20.2.1 Processing through modeling
20.2.1.1 Parametric stimulus encoding
20.2.1.2 Nonparametric stimulus encoding
20.3 Closing the loop
References
21 Safety and regulatory issues for clinical testing
21.1 Relationships of quality, regulatory, safety, and testing with clinical studies
21.2 Medical device lifecycle phases and design control
21.3 Verification and validation testing
21.4 Regulatory paths for clinical studies in the United States
21.5 Regulatory paths for device commercialization in the United States
21.6 Comparison of European Union and United States regulatory processes
21.6.1 Clinical studies in the European Union
21.6.2 Device commercialization in the European Union
References
Index
Back Cover